Business Model Risk Analysis: Predicting the Probability of Business Network Profitability - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2013

Business Model Risk Analysis: Predicting the Probability of Business Network Profitability

Pontus Johnson
  • Fonction : Auteur
  • PersonId : 1002372
Maria Eugenia Iacob
  • Fonction : Auteur
  • PersonId : 998713
Margus Välja
  • Fonction : Auteur
  • PersonId : 1002373
Marten Van Sinderen
  • Fonction : Auteur
  • PersonId : 998714
Christer Magnusson
  • Fonction : Auteur
  • PersonId : 1002374
Tobias Ladhe
  • Fonction : Auteur
  • PersonId : 1002375

Résumé

In the design phase of business collaboration, it is desirable to be able to predict the profitability of the business-to-be. Therefore, techniques to assess qualities such as costs, revenues, risks, and profitability have been previously proposed. However, they do not allow the modeler to properly manage uncertainty with respect to the design of the considered business collaboration. In many real collaboration projects today, uncertainty regarding the business’ present or future characteristics is so significant that ignoring it becomes problematic. In this paper, we propose an approach based on the Predictive, Probabilistic Architecture Modeling Framework (P2AMF), capable of advanced and probabilistically sound reasoning about profitability risks. The P2AMF-based approach for profitability risk prediction is also based on the e3-value modeling language and on the Object Constraint Language (OCL). The paper introduces the prediction and modeling approach, and a supporting software tool. The use of the approach is illustrated by means of a case.
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Dates et versions

hal-01474205 , version 1 (22-02-2017)

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Pontus Johnson, Maria Eugenia Iacob, Margus Välja, Marten Van Sinderen, Christer Magnusson, et al.. Business Model Risk Analysis: Predicting the Probability of Business Network Profitability. 5th International Working Conference on Enterprise Interoperability (IWEI), Mar 2013, Enschede, Netherlands. pp.118-130, ⟨10.1007/978-3-642-36796-0_11⟩. ⟨hal-01474205⟩
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